Update app.py

app.py

@@ -19,7 +19,7 @@ def segment_everything(image):
     if isinstance(image, np.ndarray):
         image = Image.fromarray(image)
     
-    inputs = processor(text=["object"], images=[image], padding="max_length", return_tensors="pt").to(device)
+    inputs = processor(text=["object"], images=image, padding="max_length", return_tensors="pt").to(device)
     with torch.no_grad():
         outputs = model(**inputs)
     preds = outputs.logits.squeeze().sigmoid().cpu()
@@ -35,7 +35,7 @@ def segment_box(image, x1, y1, x2, y2):
     
     x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)
     cropped_image = image[y1:y2, x1:x2]
-    inputs = processor(text=["object"], images=[Image.fromarray(cropped_image)], padding="max_length", return_tensors="pt").to(device)
+    inputs = processor(text=["object"], images=Image.fromarray(cropped_image), padding="max_length", return_tensors="pt").to(device)
     with torch.no_grad():
         outputs = model(**inputs)
     preds = outputs.logits.squeeze().sigmoid().cpu()
@@ -57,7 +57,7 @@ def update_image(image, segmentation):
     
     seg_pil = Image.fromarray(segmentation).convert('RGBA')
     
-    if image_pil.size != seg_pil.size:
+    if image_pil.size!= seg_pil.size:
         seg_pil = seg_pil.resize(image_pil.size, Image.NEAREST)
     
     blended = Image.blend(image_pil.convert('RGBA'), seg_pil, 0.5)
@@ -96,4 +96,4 @@ with gr.Blocks() as demo:
         outputs=[output_image]
     )
 
-demo.launch()
+demo.launch()